SHARPCLAW: Synteny, Homology And Repeat Pre-curation for Chromosome-Level Assembly Workflows

I’ve been a recovering acronymiser for some time, with the last few bioinformatics given more punny names, like Diploidocus, Taxolotl, Telociraptor and SynBad. But I was pushed for time preparing a conference poster and needed a name for a new workflow, and SHARPCLAW - Synteny, Homology And Repeat Pre-curation for Chromosome-Level Assembly Workflows - was born. I’ve not yet crow-barred in additional meaning, so for now this has definite ad hoc status.

FUBAR - Fast Unconstrained Bayesian AppRoximation

From the authors that brought you BUSTED (Branch-site Unrestricted Statistical Test for Episodic Diversification), behold FUBAR: Fast Unconstrained Bayesian AppRoximation. (Doubly from the authors in this case, as the first author gave the tip-off.)

Despite it’s intranym status, FUBAR gets an extra geek hat-tip for being a homonym of “foo bar”. (Although in looking that up, I came across the original FUBAR acronym, which is hopefully not reflective of their method!)

Abstract

Model-based analyses of natural selection often categorize sites into a relatively small number of site classes. Forcing each site to belong to one of these classes places unrealistic constraints on the distribution of selection parameters, which can result in misleading inference due to model misspecification. We present an approximate hierarchical Bayesian method using a Markov chain Monte Carlo (MCMC) routine that ensures robustness against model misspecification by averaging over a large number of predefined site classes. This leaves the distribution of selection parameters essentially unconstrained, and also allows sites experiencing positive and purifying selection to be identified orders of magnitude faster than by existing methods. We demonstrate that popular random effects likelihood methods can produce misleading results when sites assigned to the same site class experience different levels of positive or purifying selection–an unavoidable scenario when using a small number of site classes. Our Fast Unconstrained Bayesian AppRoximation (FUBAR) is unaffected by this problem, while achieving higher power than existing unconstrained (fixed effects likelihood) methods. The speed advantage of FUBAR allows us to analyze larger data sets than other methods: We illustrate this on a large influenza hemagglutinin data set (3,142 sequences). FUBAR is available as a batch file within the latest HyPhy distribution (http://www.hyphy.org), as well as on the Datamonkey web server (http://www.datamonkey.org/).

• Murrell B, Moola S, Mabona A, Weighill T, Sheward D, Kosakovsky Pond SL & Scheffler K (2013). FUBAR: a fast, unconstrained bayesian approximation for inferring selection. Mol Biol Evol. 30(5):1196-205. PMID: 23420840

BUSTED - Branch-site Unrestricted Statistical Test for Episodic Diversification

This paper popped up in my PubCrawler feed today:

Murrell B et al. (2015). Gene-wide identification of episodic selection. Mol Biol Evol. 2015 Feb 19. pii: msv035.

We present BUSTED, a new approach to identifying gene-wide evidence of episodic positive selection, where the non-synonymous substitution rate is transiently greater than the synonymous rate. BUSTED can be used either on an entire phylogeny (without requiring an a priori hypothesis regarding which branches are under positive selection) or on a pre-specified subset of foreground lineages (if a suitable a priori hypothesis is available). Selection is modeled as varying stochastically over branches and sites, and we propose a computationally inexpensive evidence metric for identifying sites under episodic positive selection on any foreground branches. We compare BUSTED to existing models on simulated and empirical data. An implementation is available on www.datamonkey.org/busted, with a widget allowing the interactive specification of foreground branches.

From the Introduction, we find that BUSTED is indeed an orca-worthy contrived acronym: BUSTED - Branch-site Unrestricted Statistical Test for Episodic Diversification.

SANTA - Spatial Analysis of NeTwork Associations

A festive bioinformatics acronym today: SANTA - Spatial Analysis of NeTwork Associations. The authors don't make a big deal of the acronym in the paper but it seemed contrived enough for a Christmas ORCA entry.

Abstract

Linking networks of molecular interactions to cellular functions and phenotypes is a key goal in systems biology. Here, we adapt concepts of spatial statistics to assess the functional content of molecular networks. Based on the guilt-by-association principle, our approach (called SANTA) quantifies the strength of association between a gene set and a network, and functionally annotates molecular networks like other enrichment methods annotate lists of genes. As a general association measure, SANTA can (i) functionally annotate experimentally derived networks using a collection of curated gene sets and (ii) annotate experimentally derived gene sets using a collection of curated networks, as well as (iii) prioritize genes for follow-up analyses. We exemplify the efficacy of SANTA in several case studies using the S. cerevisiae genetic interaction network and genome-wide RNAi screens in cancer cell lines. Our theory, simulations, and applications show that SANTA provides a principled statistical way to quantify the association between molecular networks and cellular functions and phenotypes. SANTA is available from http://bioconductor.org/packages/release​/bioc/html/SANTA.html.

Ref: Cornish AJ & Markowetz F (2014) SANTA: Quantifying the Functional Content of Molecular Networks. PLoS Comput Biol 10(9): e1003808.

MUSIC - MUltiScale enrIchment Calling

Over on the ACGT blog, Keith Bradnam has another JABBA Award (and a nice new JABBA logo):

MUSIC - Multiscale Enrichment Calling.

I'm not sure what the connection between MUSIC and ChIP-Seq is but the authors seemed pretty determined. His post is actually a twofer, as it also draws attention to an equally contrived an unfathomable intranym:

MuSiC - Multiple Sequence Alignment with Constraints

Read more at Keith’s blog!

PEPPER - Protein complex Expansion using Protein-Protein intERactions

Another offering from the ever-fruitful world of bioinformatics today - with a fruit, fittingly enough.

PEPPER - Protein complex Expansion using Protein-Protein intERactions - pulls out all the stops when it comes to contriving a functional word, skipping words and using internal letters.

For the curious, PEPPER is available from the Cytoscape App Store and is:

“designed to identify protein complexes as densely connected subnetworks from seed lists of proteins derived from proteomic studies. Pepper identifies connected subgraph by using multi-objective optimization involving two functions: (i) the coverage, a solution must contain as many proteins from the seed as possible, (ii) the density, the proteins of a solution must be as connected as possible, using only interactions from a proteome-wide interaction network.”

Despite its use of “seed lists”, I don’t think there is a direct connection with peppers, so PEPPER is being classified as an ad hoc intranym.

I’m not sure if there’s a bigger version of the logo available but if you look carefully, you can see the little chilli peppers.

Winterhalter C et al. (2014) PEPPER: cytoscape app for protein complex expansion using protein-protein interaction networks. Bioinformatics. Aug 18. pii: btu517. [Epub ahead of print]

WImpiBLAST - Web Interface for mpiBLAST

Although BLAST is a deserved ORCAcronym in its own right, it is also notable for the number of spin-offs and add-ons that it has produced. One such program is mpiBLAST, an open-source parallelisation of BLAST. This is turn has spawned WImpiBLAST - Web Interface for mpiBLAST. I’m not sure if WImpiBLAST deserves a new “anti hoc” class of acronym, as parallelisation of BLAST on a supercomputer is anything but wimpy. Ad hoc will do for now.

You can find out more at RNA-Seq Blog or the paper:

• Sharma P & Mantri SS (2014) “WImpiBLAST: Web Interface for mpiBLAST to Help Biologists Perform Large-Scale Annotation Using High Performance Computing.” PLoS ONE 9(6): e101144.

BLAST - Basic Local Alignment Search Tool

If there is one bioinformatics program that every biologist has heard of, it is BLAST: Basic Local Alignment Search Tool. In fact, BLAST is so popular and famous that many people probably don’t know that it is an acronym nor what it stands for; “to BLAST” has become a verb in common use. For non-biologists, BLAST is a homology search tool, which means that it finds similarities between biological (nucleotide or protein) sequences, and biologists will frequently “BLAST a sequence against a database” to find similar sequences.

The original BLAST algorithm is pretty old, which is part of the reason for its widespread fame. I’m not sure of the stats but the original Altschul et al. (1990) paper must be one of the most cited of all time.

• Altschul S, Gish W, Miller W, Myers E & Lipman D (1990). “Basic local alignment search tool”. Journal of Molecular Biology 215 (3): 403–410.

Certainly a worth addition to ORCA. (Although the main motivation for adding it is for the next post!) Given that BLAST works by fragmenting the query sequence into pieces for the initial search, I think that it rates at least as a post hoc.

MFSPSSMpred - Masked, Filtered and Smoothed Position-Specific Scoring Matrix-based predictor

Today’s post is a bit odd, as it is an anti-ORCA acronym. There is a reason why contrived acronyms exist, and I think that MFSPSSMpred is a prime example. The acronym itself is almost informative, although it fails to identify what it is trying to predict. (Short molecular recognition features in this case.) Still, imagine yourself in a lab meeting, trying to tell your supervisor which prediction tool you were using from memory!

MFSPSSMpred does have one thing going for it, though, and that’s Google-friendliness. Providing you spell it right, that is!

P.S. Whilst Googling MFSPSSMpred, I discovered that OCTAGON-winning Keith Bradnam got there first and MFSPSSMpred is a JABBA Award winner!

miRCat - miRNA Categoriser

I am currently writing some lectures on RNA biology and came across the charmingly named miRCat: miRNA Categoriser.

This is a meta-acronym, with miRNA being short for microRNA (often abbreviated further to "miR" and pronounced “meer”, hence the logo) and RNA itself an acronym for Ribonucleic Acid).

miRCat is a tool to identify miRNAs in high-throughput small RNA sequence data… miRCat takes a FASTA file of small RNA reads as input and will map them to a reference genome… The tool then looks at genomic hit distribution patterns and secondary structure of genomic regions corresponding to sRNA hits and will predict miRNAs and their precursor structures.

Given the homophonic aspect of the acronym, I reckon this counts as pre hoc. As far as I am aware, “Categoriser” is not even a real (English) word, so this is definitely acronym contrivance worth of ORCA.

TrIPE - T. rex International Paleontonomics Experiment (TrIPE)

The T. rex International Paleontonomics Experiment (TrIPE) was responsible for the Tyrannosaurus rex draft genome, released on 1st April 2003 and described as “the genetic blueprint for the most important of the dinosaurs used in genetics today”. Unfortunately, it is no longer available on the Ensembl genome database, having been withdrawn for being totally fabricated. ☺

[Image from Wikimedia Commons]

LAMARC - Likelihood Analysis with Metropolis Algorithm using Random Coalescence

A post on the Evolution Directory (EvolDir) altered me to another classic bioinformatics acronym today: LAMARC - Likelihood Analysis with Metropolis Algorithm using Random Coalescence, which has just been updated to version 2.1.9.

“LAMARC is a program which estimates population-genetic parameters such as population size, population growth rate, recombination rate, and migration rates. It approximates a summation over all possible genealogies that could explain the observed sample, which may be sequence, SNP, microsatellite, or electrophoretic data. LAMARC and its sister program Migrate are successor programs to the older programs Coalesce, Fluctuate, and Recombine, which are no longer being supported. The programs are memory-intensive but can run effectively on workstations; we support a variety of operating systems.”

I was all prepared to leap straight in and award LAMARC the coveted pre hoc acronym category for contriving a domain-relevant acronym when I was somewhat halted in my tracks by this statement on the website:

“The LAMARC package is not in any immediate sense derived from the work of Jean Baptiste Pierre Antoine de Monet, Chevalier de Lamarck(1744-1829). The similarity of names is mostly accidental. But all evolutionary biologists do owe him a debt. Lamarck is an unfairly maligned figure. In addition to being one of the greatest figures of invertebrate biology, he was one of the founders (with Buffon) of the theory of evolution, and the first to propose a mechanism for evolution. You may want to read more about his life and work.”

I am not entirely convinced that the similarity of the names can really be “mostly accidental”, even if that particular acronym did leap out at them once they had the keywords. Either way, the evolutionary link is clear and so, accident or not, I think this warrants a pre hoc rather than post hoc. (Now go and read up on Lamarck.)

More JABBA Awards at keithbradnam.com

Just a quick post to note that Keith Bradnam has a few more contrived bioinformatics algorithms at over at keithbradnam.com for another round of JABBA (Just Another Bogus Bioinformatics Acronym) awards. I’ll no doubt steal them for ORCA once a decent amount of time has passed! :op (Actually, they’ve been up for a couple of weeks already, I was just slow to spot them.)

ADAN - prediction of protein-protein interAction of moDular domAiNs

The ADAN Database - prediction of protein-protein interAction of moDular domAiNs - breaks the rules, really, as it is not technically an acronym. To be honest, I am not really sure what it is but it seemed so contrived that it warranted an ORCA entry. To add to the confusion, I do not know what “Adan” (the word rather than the database) is nor its relevance to protein-protein interactions, which is one of my own research areas.

As the database seems to be hosted by Universidad Miguel Hernández in Spain, the only thing I can think is that it is a backronym homage to Spanish footballer, Antonio Adán!

h/t: Nico.

PICRUSt - Phylogenetic Investigation of Communities by Reconstruction of Unobserved States

I think that my favourite talk from the 1st International Environmental ‘Omics Synthesis Conference was the Keynote address by Jack Gilbert on the Earth Microbiome Project and other cool microbial metagenomic/metagenetic stuff. It also featured an impressively contrived acronym:

PICRUSt - Phylogenetic Investigation of Communities by Reconstruction of Unobserved States.

Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community’s functional capabilities. Here we describe PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this ‘predictive metagenomic’ approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available.

Langille MGI et al. (2013). Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature Biotechnology 31, 814–821.

GOBLET - Global Organisation for Bioinformatics Learning, Education & Training

I’m at the 1st International Environmental Omics Synthesis (iEOS) Conference conference in Cardiff, which means (a) very little time for posting, and (b) a wealth of acronyms on display. A particularly notable contribution from one of the earlier sessions was GOBLET: Global Organisation for Bioinformatics Learning, Education & Training.

GOBLET, the Global Organisation for Bioinformatics Learning, Education and Training, is a legally registered foundation. Its mission is to:

1. Provide a global, sustainable support and networking structure for bioinformatics educators/trainers and students/trainees (including a training portal for sharing materials, tools, tips and techniques; guidelines and best practice documents; facilities to help train the trainers; and offering different learning pathways for different types of learner)

2. Facilitate capacity development in bioinformatics in all countries

3. Develop standards and guidelines for bioinformatics education and training

4. Act as a hub for fund gathering

5. Reach out to, amongst others, teachers at high schools, to bridge the gap to the next generation of bioinformaticians, and

6. Foster the international community of B3CB trainers

As well as the natty acronym, it could be quite useful.

BEDASSLE - Bayesian Estimation of Differentiation in Alleles by Spatial Structure and Local Ecology

Courtesy of Graham Coop on Twitter comes BEDASSLE: Bayesian Estimation of Differentiation in Alleles by Spatial Structure and Local Ecology.

"This is a method [Gideon Bradburd] worked on in collaboration with Peter Ralph and Graham Coop. It allows users to quantify the relative contributions of geographic and environmental distance to patterns of genetic differentiation."

This is a very solid ad hoc contrived acronym - making a word that is easy to pronounce but also (thanks to the altered spelling) easy to Google whilst not sounding too contrived. Hats off to Gideon, Peter and Graham. (I'm not really sure that I understand the connection to the logo, though!)

ORCAE - Online Resource for Community Annotation of Eukaryotes

Another contribution from top ORCA spotter, Bethan, and another animal-themed genome resource. This one was too good to ignore: ORCAE - Online Resource for Community Annotation of Eukaryotes:

ORCAE is an online genome annotation resource offering users the necessary tools and information to validate and correct gene annotations. The system is build on the wiki philosophy, all modifications to a certain gene are stored and can be found back in the annotation history of that gene. To be able to modify genes however you will need to have a user account. Anonymous users can browse the public genomes but don’t have editing rights.

Sterck L, Billiau K, Abeel T, Rouzé P & Van de Peer Y (2012). ORCAE: online resource for community annotation of eukaryotes. Nat. Methods 9:1041.

JABBA - Just Another Bogus Bioinformatics Acronym

As already noted in the recent Biostars post, my own field of bioinformatics is particularly bad (or good, depending on your point of view,) at spawning contrived acronyms. Sometimes this works. Sometimes it doesn’t. Sometimes, you get the feeling that people are trying a little too hard.

Keith Bradnam has a long and illustrious career in bioinformatics - I first met him when I was a PhD student in Nottingham in the late ’90s, where he was probably the number one local bioinformatics guru. As a result, he has seen more that his fair share of acronym atrocities committed in the name of science. This has resulted in his creation of the Just Another Bogus Bioinformatics Acronym (JABBA) Award.

I won’t reveal the winner of the inaugural JABBA award here - you’ll have to read Keith’s post, linked above, to find out - but ORCA is sufficiently impressed with Keith’s commitment to using acronyms to fight acronyms, that he is being awarded the inaugural Outstanding Contribution To Acronym Generation Or Notoriety (OCTAGON) award. Congratulations, Keith!

GARFIELD - Genome Annotation Resource FIELDs (a cat genome browser)

This seemed like an appropriate “Caturday” post. GARFIELD is short for Genome Annotation Resource FIELDs and is a real pre hoc contrived acronym, for this is a cat genome browser. It’s a shame that there is nothing inherently feline about the expanded name, which suggests that sacrifices were made in pursuit of the desired acronym, but it’s still a worthy effort.

As well as its clear ORCA credentials, GARFIELD has a special place in ORCA as it was an email about it from a friend and collaborator that first brought the idea of resuscitating ORCA to mind. Thanks, Bethan!

Pontius JU & O’Brien SJ (2007), Genome Annotation Resource Fields—GARFIELD: A Genome Browser for Felis catus. J Hered 98 (5): 386-389.